Delhivery AI vs Celonis

By valuation, Celonis is the larger company at $13B versus $1.7B — a 7.6x difference. Size can also be measured by team: Delhivery AI employs 5000+ people while Celonis has 1000+ employees.

Celonis has raised more in total funding at $1.4B, compared to Delhivery AI's $1B — a gap of $400M.

Both Delhivery AI and Celonis share the same Awaira Score of 90/100. The Awaira Score is a composite metric that factors in valuation, total funding raised, company stage, employee count, and market category.

Delhivery AI was founded by Sahil Barua in 2011. Celonis was founded by Alexander Rinke in 2011. Visit each company's profile on Awaira for a full founder biography.

Delhivery AI: Delhivery is India's largest publicly listed logistics and supply chain services company, operating an AI-powered platform that coordinates end-to-end parcel delivery, freight forwarding, warehousing, and cross-border logistics through a combination of proprietary technology, owned infrastructure, and a partner network spanning over 17,000 PIN codes. The company's AI systems optimize route planning, dynamic pricing, capacity allocation, and network design across millions of daily shipments.\n\nListed on the NSE and BSE, Delhivery raised over $1B in equity funding prior to its IPO and commands a market capitalization reflecting its position as India's dominant third-party logistics provider. The company serves thousands of direct e-commerce, retail, and enterprise clients and processes hundreds of millions of shipments annually.\n\nDelhivery's scale in Indian logistics creates a data advantage that compounds — each additional shipment improves the AI models that drive route optimization, delivery time prediction, and network capacity planning. As Indian e-commerce continues to expand and logistics infrastructure investment intensifies, Delhivery's technology platform and network scale position it as the default logistics intelligence layer for the Indian supply chain. Celonis: Celonis builds a process mining and execution management platform that uses machine learning to extract, visualise, and optimise business processes from event log data in enterprise systems including SAP, Oracle, Salesforce, and ServiceNow. The Munich company platform connects to enterprise software transaction records, reconstructs actual business process flows from data, identifies inefficiencies and compliance deviations, and provides AI-powered recommendations for process improvement.\n\nThe company raised approximately $1.4 billion including a $1 billion Series D round in 2021 from investors including Arena Holdings, Durable Capital, and T. Rowe Price, valuing it at $13 billion and making it one of Germany most valuable private technology companies. Celonis counts over 1,000 enterprise clients including Siemens, Uber, 3M, and Vodafone, with large deployments across order-to-cash, procure-to-pay, and accounts payable processes generating measurable working capital improvements and operational cost reductions.\n\nCelonis created the process mining software category and competes against SAP Signavio, IBM Process Mining, and Minit in a market it largely invented. The company has expanded from analytical process mining tools into execution management, embedding AI recommendations directly into enterprise workflows rather than producing reports for human review. This execution layer differentiates Celonis from pure analytics vendors and creates a stickier product that becomes embedded in operational processes rather than consumed as a standalone analysis tool.

Both Delhivery AI and Celonis were founded in the same year — 2011. Despite sharing a founding year, they may have launched at different times within that year, which can matter in fast-moving AI markets.

Delhivery AI has approximately 5000+ employees, while Celonis has approximately 1000+. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Delhivery AI and Celonis are direct competitors — both operate in the Enterprise AI space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.